Image detection method, image detection device and mobile terminal
An image detection and to-be-detected technology, applied in the field of image processing, can solve problems such as inability to achieve high-precision detection of target objects, achieve accurate and rapid target detection, meet real-time requirements, and achieve high-precision positioning.
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Embodiment 1
[0044] An image detection method provided in Embodiment 1 of the present application is described below, please refer to the attached figure 1 , the image detection method provided in Embodiment 1 of the present application includes:
[0045] In step S101, obtain the reference picture of the video to be detected;
[0046] In this embodiment of the application, the above-mentioned video to be detected may be a video stored locally, such as a TV series, a variety show, etc. downloaded by the user; , news programs, cartoons, etc. watched online; it can also be the video that the user turns on the camera of the mobile terminal to record or the preview screen after the mobile terminal starts the camera or the video camera, and the type of the video to be detected is not limited here.
[0047] The reference picture above can be any frame of the video to be detected. The image detection method provided in the embodiment of the present application can detect the target object in the ...
Embodiment 2
[0084] Another image detection method provided by the embodiment of this application is described below, please refer to the attached image 3 , the image detection method of Embodiment 2 of the present application includes:
[0085] In step S201, obtain the reference picture of the video to be detected;
[0086] In step S202, use the trained convolutional neural network model to perform target object detection on the reference picture, and obtain a detection result;
[0087] In the embodiment of the present application, the above steps S201 and S202 are the same as steps S101 and S102 in the first embodiment. For details, please refer to the description of the first embodiment, which will not be repeated here.
[0088] In step S203, it is judged whether the detection result indicates that the reference picture contains one or more target objects; if not, execute step S204; if yes, execute step S205;
[0089] In step S204, set a picture that is a preset number of frames away...
Embodiment 3
[0112] Another image detection method provided by the embodiment of this application is described below, please refer to the attached Figure 5 , the image detection method of Embodiment 3 of the present application includes:
[0113] In step S301, obtain the reference picture of the video to be detected;
[0114] In step S302, use the trained convolutional neural network model to perform target object detection on the reference picture, and obtain a detection result;
[0115] In step S303, it is judged whether the detection result indicates that the reference picture contains one or more target objects; if not, execute step S304; if yes, execute step S305;
[0116] In step S304, set a picture that is a preset number of frames away from the reference picture as the reference picture, and return to step S302;
[0117] In step S305, acquire the picture to be detected which is separated from the reference picture by a preset number of frames in the video to be detected;
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